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Found 8 papers, 1 papers with code
DreamWalk: Style Space Exploration using Diffusion Guidance
Text-conditioned diffusion models can generate impressive images, but fall short when it comes to fine-grained control.
Dimensions of Motion: Monocular Prediction through Flow Subspaces
We introduce a way to learn to estimate a scene representation from a single image by predicting a low-dimensional subspace of optical flow for each training example, which encompasses the variety of possible camera and object movement.
Deep survival analysis with longitudinal X-rays for COVID-19
Time-to-event analysis is an important statistical tool for allocating clinical resources such as ICU beds.
OCONet: Image Extrapolation by Object Completion
Existing methods struggle to extrapolate images with salient objects in the foreground or are limited to very specific objects such as humans, but tend to work well on indoor/outdoor scenes.
Object-centered image stitching
Image stitching is typically decomposed into three phases: registration, which aligns the source images with a common target image; seam finding, which determines for each target pixel the source image it should come from; and blending, which smooths transitions over the seams.
Robust image stitching with multiple registrations
Here, we observe that the use of a single registration often leads to errors, especially in scenes with significant depth variation or object motion.
Learning to Autofocus
Autofocus is an important task for digital cameras, yet current approaches often exhibit poor performance.
Channel selection using Gumbel Softmax
Important applications such as mobile computing require reducing the computational costs of neural network inference.
